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On the uniqueness of the infinite cluster and the cluster density in the Poisson driven random connection model

Chebunin, Mikhail; Last, Günter ORCID iD icon 1
1 Institut für Stochastik (STOCH), Karlsruher Institut für Technologie (KIT)

Abstract:

We consider a random connection model (RCM) on a general space driven by a Poisson
process whose intensity measure is scaled by a parameter t ≥ 0. We say that the infinite clusters are deletion stable if the removal of a Poisson point cannot split a cluster in two or more infinite clusters. We prove that this stability together with a natural irreducibility assumption implies uniqueness of the infinite cluster. Conversely, if the infinite cluster is unique then this stability property holds. Several criteria for irreducibility will be established. We also study the analytic properties of expectations of functions of clusters as a function of t. In particular we show that the position dependent cluster density is differentiable. A significant part of this paper is devoted to the important case of a stationary marked RCM (in Euclidean space), containing
the Boolean model with general compact grains and the so-called weighted RCM as special cases. In this case we establish differentiability and a convexity property of the cluster density κ(t). These properties are crucial for our proof of deletion stability of the infinite clusters but are also of interest in their own right. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000190354
Veröffentlicht am 09.02.2026
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Stochastik (STOCH)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 01.01.2025
Sprache Englisch
Identifikator ISSN: 1083-6489
KITopen-ID: 1000190354
Erschienen in Electronic Journal of Probability
Verlag Institute of Mathematical Statistics (IMS)
Band 30
Seiten Article no: 175
Schlagwörter random connection model; Poisson process; percolation; Margulis–Russo formula;, cluster density; uniqueness of infinite cluster
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